Upload 11 files

analysis/chart_analyzer.py

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+import ollama
+from src.model.vision_model import ChartVisionModel
+
+class ChartAnalyzer:
+    def __init__(self):
+        self.vision_model = ChartVisionModel()
+        self.client = ollama.Client()
+    
+    def analyze_full(self, chart_image, pattern_images, indicator_charts, historical_data):
+        vision_analysis = self.vision_model.analyze_chart(chart_image)
+        
+        system_prompt = """Analyze this technical chart with all patterns and indicators:
+        1. Pattern Analysis (300+ patterns)
+        2. Indicator Analysis
+        3. Current Chart Analysis
+        4. Movement Predictions
+        Provide detailed analysis for each component."""
+        
+        analysis = self.client.generate(
+            model="llama3.2-vision:latest",
+            prompt=system_prompt,
+            images=[chart_image] + pattern_images
+        )
+        
+        return {
+            'patterns': self._analyze_patterns(pattern_images),
+            'indicators': self._analyze_indicators(indicator_charts),
+            'predictions': self._generate_predictions(analysis)
+        }

analysis/chart_processor.py

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+from src.model.vision_model import ChartVisionModel
+import cv2
+import numpy as np
+
+class ChartProcessor:
+    def __init__(self):
+        self.vision_model = ChartVisionModel()
+    
+    def preprocess_image(self, image):
+        # Image preprocessing for analysis
+        return image
+    
+    def detect_patterns(self, image):
+        # Pattern detection logic
+        return []
+    
+    def analyze_indicators(self, image):
+        # Technical indicator analysis
+        return {}
+    
+    def process_chart(self, image):
+        preprocessed = self.preprocess_image(image)
+        patterns = self.detect_patterns(preprocessed)
+        indicators = self.analyze_indicators(preprocessed)
+        
+        return {
+            'patterns': patterns,
+            'indicators': indicators
+        }

analysis/indicator_generator.py

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+import ollama
+from lightweight_charts import Chart
+
+class IndicatorGenerator:
+    def __init__(self):
+        self.client = ollama.Client()
+        self.code_model = "codellama:latest"
+        self.indicators = [
+            'rsi', 'macd', 'bollinger_bands', 'moving_averages',
+            'stochastic', 'atr', 'volume_profile'
+        ]
+    
+    def generate_all_indicators(self, historical_data):
+        indicator_charts = []
+        for indicator in self.indicators:
+            # Generate code for indicator using CodeLlama
+            code_prompt = f"Generate Lightweight Charts code for {indicator} indicator with proper styling and configuration"
+            code_response = self.client.generate(
+                model=self.code_model,
+                prompt=code_prompt
+            )
+            
+            # Create chart using generated code
+            chart = Chart()
+            chart.set(code_response)  # Applies the generated configuration
+            chart.add_data(historical_data)
+            
+            indicator_charts.append(chart)
+        
+        return indicator_charts
+
+    def _create_indicator_chart(self, data, indicator_type):
+        chart = Chart()
+        # Specific indicator configurations using Lightweight Charts
+        chart.add_indicator(indicator_type, data)
+        return chart

analysis/pattern_generator.py

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+import ollama
+from lightweight_charts import Chart
+
+class PatternGenerator:
+    def __init__(self):
+        self.client = ollama.Client()
+        self.code_model = "codellama:latest"
+        self.patterns = [
+            'head_and_shoulders', 'double_top', 'double_bottom',
+            'triangle', 'channel', 'fibonacci', 'wedge', 'flag',
+            'pennant', 'cup_and_handle', 'rounding_bottom'
+            # Will expand to 300+ patterns
+        ]
+    
+    def generate_all_patterns(self, chart_image, historical_data):
+        pattern_charts = []
+        for pattern in self.patterns:
+            # Generate pattern drawing code using CodeLlama
+            code_prompt = f"Generate Lightweight Charts code to draw {pattern} pattern with proper styling and technical analysis markers"
+            code_response = self.client.generate(
+                model=self.code_model,
+                prompt=code_prompt
+            )
+            
+            # Create chart with pattern overlay
+            chart = Chart()
+            chart.set(code_response)
+            chart.add_data(historical_data)
+            
+            pattern_charts.append(chart)
+        
+        return pattern_charts

app.py

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+import sys
+import os
+current_dir = os.path.dirname(os.path.abspath(__file__))
+project_root = os.path.dirname(current_dir)
+sys.path.append(project_root)
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+import gradio as gr
+from src.analysis.chart_processor import ChartProcessor
+from src.analysis.pattern_generator import PatternGenerator
+from src.analysis.indicator_generator import IndicatorGenerator
+from src.analysis.chart_analyzer import ChartAnalyzer
+from src.data.market_data import MarketData
+
+def analyze_full_chart(chart_image, symbol):
+    market_data = MarketData()
+    historical_data = market_data.fetch_ohlcv(symbol)
+    
+    pattern_gen = PatternGenerator()
+    pattern_images = pattern_gen.generate_all_patterns(chart_image, historical_data)
+    
+    indicator_gen = IndicatorGenerator()
+    indicator_charts = indicator_gen.generate_all_indicators(historical_data)
+    
+
+    processor = ChartProcessor()
+    results = processor.process_chart(chart_image)
+
+    analyzer = ChartAnalyzer()
+    analysis_results = analyzer.analyze_full(
+        chart_image=chart_image,
+        pattern_images=pattern_images,
+        indicator_charts=indicator_charts,
+        historical_data=historical_data
+    )
+    
+    return {
+        'pattern_analysis': analysis_results.patterns,
+        'indicator_analysis': analysis_results.indicators,
+        'predictions': analysis_results.predictions,
+        'interactive_charts': indicator_charts,
+        'chart_analysis':results,
+    }
+
+interface = gr.Interface(
+    fn=analyze_full_chart,
+    inputs=[
+        gr.Image(type="pil", label="Chart Image"),
+        gr.Textbox(label="Symbol")
+    ],
+    outputs=[
+        gr.Gallery(label="Pattern Overlays"),
+        gr.Gallery(label="Indicator Charts"),
+        gr.JSON(label="Analysis Results"),
+        gr.Plot(label="Interactive Indicators")
+    ]
+)
+
+interface.launch()

data/market_data.py

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+import requests
+import pandas as pd
+from datetime import datetime, timedelta
+
+class MarketData:
+    def __init__(self):
+        self.base_url = "YOUR_MARKET_DATA_API_ENDPOINT"
+        
+    def fetch_ohlcv(self, symbol, timeframe='1d'):
+        """
+        Fetch OHLCV data for given symbol
+        Returns: DataFrame with columns [timestamp, open, high, low, close, volume]
+        """
+        endpoint = f"{self.base_url}/historical/{symbol}"
+        params = {
+            'timeframe': timeframe,
+            'limit': 365  # Last year of data
+        }
+        
+        response = requests.get(endpoint, params=params)
+        data = response.json()
+        
+        df = pd.DataFrame(data)
+        df['timestamp'] = pd.to_datetime(df['timestamp'])
+        return df
+    
+    def get_latest_price(self, symbol):
+        endpoint = f"{self.base_url}/price/{symbol}"
+        response = requests.get(endpoint)
+        return response.json()['price']

model/vision_model.py

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+import ollama
+from PIL import Image
+
+class ChartVisionModel:
+    def __init__(self):
+        self.client = ollama.Client()
+        self.model = "llava:34b"  # Using LLaVA for vision analysis
+    
+    def analyze_chart(self, image):
+        response = self.client.generate(
+            model=self.model,
+            prompt="Analyze this technical chart in detail",
+            images=[image]
+        )
+        return response
+

requirements.txt

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+gradio>=4.0.0
+torch>=2.0.0
+transformers>=4.30.0
+python-ollama>=0.1.0
+Pillow>=10.0.0
+huggingface-hub>=0.19.0
+python-dotenv>=1.0.0
+fastapi
+uvicorn
+gradio
+huggingface-hub
+transformers
+torch
+lightweight-charts
+pandas
+numpy
+requests
+python-multipart
+ollama
+python-dotenv
+plotly
+opencv-python
+pillow